{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 鸢尾花数据集使用案例"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>.container{width:100% !important;}</style>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 宽屏幕显示\n",
    "from IPython.core.display import display, HTML\n",
    "display(HTML('<style>.container{width:100% !important;}</style>'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 导入数据可视化模块\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn import datasets\n",
    "\n",
    "%matplotlib inline\n",
    "plt.style.use({\"figure.figsize\":(10,8)})\n",
    "\n",
    "sns.set_style(\"whitegrid\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sepal.Length</th>\n",
       "      <th>Sepal.Width</th>\n",
       "      <th>Petal.Length</th>\n",
       "      <th>Petal.Width</th>\n",
       "      <th>Species</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>5.4</td>\n",
       "      <td>3.9</td>\n",
       "      <td>1.7</td>\n",
       "      <td>0.4</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.4</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.3</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>4.4</td>\n",
       "      <td>2.9</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.1</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>5.4</td>\n",
       "      <td>3.7</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>4.8</td>\n",
       "      <td>3.4</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>4.8</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.1</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>4.3</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.1</td>\n",
       "      <td>0.1</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>5.8</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.2</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>5.7</td>\n",
       "      <td>4.4</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.4</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>5.4</td>\n",
       "      <td>3.9</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.4</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.3</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>5.7</td>\n",
       "      <td>3.8</td>\n",
       "      <td>1.7</td>\n",
       "      <td>0.3</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.8</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.3</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>5.4</td>\n",
       "      <td>3.4</td>\n",
       "      <td>1.7</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.7</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.4</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.3</td>\n",
       "      <td>1.7</td>\n",
       "      <td>0.5</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>4.8</td>\n",
       "      <td>3.4</td>\n",
       "      <td>1.9</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.4</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>5.2</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>5.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.6</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>6.9</td>\n",
       "      <td>3.2</td>\n",
       "      <td>5.7</td>\n",
       "      <td>2.3</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>5.6</td>\n",
       "      <td>2.8</td>\n",
       "      <td>4.9</td>\n",
       "      <td>2.0</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>7.7</td>\n",
       "      <td>2.8</td>\n",
       "      <td>6.7</td>\n",
       "      <td>2.0</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>6.3</td>\n",
       "      <td>2.7</td>\n",
       "      <td>4.9</td>\n",
       "      <td>1.8</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>6.7</td>\n",
       "      <td>3.3</td>\n",
       "      <td>5.7</td>\n",
       "      <td>2.1</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>7.2</td>\n",
       "      <td>3.2</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.8</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>6.2</td>\n",
       "      <td>2.8</td>\n",
       "      <td>4.8</td>\n",
       "      <td>1.8</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>6.1</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.9</td>\n",
       "      <td>1.8</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>6.4</td>\n",
       "      <td>2.8</td>\n",
       "      <td>5.6</td>\n",
       "      <td>2.1</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>7.2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.8</td>\n",
       "      <td>1.6</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>7.4</td>\n",
       "      <td>2.8</td>\n",
       "      <td>6.1</td>\n",
       "      <td>1.9</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>7.9</td>\n",
       "      <td>3.8</td>\n",
       "      <td>6.4</td>\n",
       "      <td>2.0</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>6.4</td>\n",
       "      <td>2.8</td>\n",
       "      <td>5.6</td>\n",
       "      <td>2.2</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>6.3</td>\n",
       "      <td>2.8</td>\n",
       "      <td>5.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>6.1</td>\n",
       "      <td>2.6</td>\n",
       "      <td>5.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>7.7</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.1</td>\n",
       "      <td>2.3</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>6.3</td>\n",
       "      <td>3.4</td>\n",
       "      <td>5.6</td>\n",
       "      <td>2.4</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>6.4</td>\n",
       "      <td>3.1</td>\n",
       "      <td>5.5</td>\n",
       "      <td>1.8</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>1.8</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>6.9</td>\n",
       "      <td>3.1</td>\n",
       "      <td>5.4</td>\n",
       "      <td>2.1</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>6.7</td>\n",
       "      <td>3.1</td>\n",
       "      <td>5.6</td>\n",
       "      <td>2.4</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>6.9</td>\n",
       "      <td>3.1</td>\n",
       "      <td>5.1</td>\n",
       "      <td>2.3</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>5.8</td>\n",
       "      <td>2.7</td>\n",
       "      <td>5.1</td>\n",
       "      <td>1.9</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>6.8</td>\n",
       "      <td>3.2</td>\n",
       "      <td>5.9</td>\n",
       "      <td>2.3</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>6.7</td>\n",
       "      <td>3.3</td>\n",
       "      <td>5.7</td>\n",
       "      <td>2.5</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>6.7</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.3</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>6.3</td>\n",
       "      <td>2.5</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>6.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.2</td>\n",
       "      <td>2.0</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>6.2</td>\n",
       "      <td>3.4</td>\n",
       "      <td>5.4</td>\n",
       "      <td>2.3</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>5.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>1.8</td>\n",
       "      <td>virginica</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>150 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Sepal.Length  Sepal.Width  Petal.Length  Petal.Width    Species\n",
       "1             5.1          3.5           1.4          0.2     setosa\n",
       "2             4.9          3.0           1.4          0.2     setosa\n",
       "3             4.7          3.2           1.3          0.2     setosa\n",
       "4             4.6          3.1           1.5          0.2     setosa\n",
       "5             5.0          3.6           1.4          0.2     setosa\n",
       "6             5.4          3.9           1.7          0.4     setosa\n",
       "7             4.6          3.4           1.4          0.3     setosa\n",
       "8             5.0          3.4           1.5          0.2     setosa\n",
       "9             4.4          2.9           1.4          0.2     setosa\n",
       "10            4.9          3.1           1.5          0.1     setosa\n",
       "11            5.4          3.7           1.5          0.2     setosa\n",
       "12            4.8          3.4           1.6          0.2     setosa\n",
       "13            4.8          3.0           1.4          0.1     setosa\n",
       "14            4.3          3.0           1.1          0.1     setosa\n",
       "15            5.8          4.0           1.2          0.2     setosa\n",
       "16            5.7          4.4           1.5          0.4     setosa\n",
       "17            5.4          3.9           1.3          0.4     setosa\n",
       "18            5.1          3.5           1.4          0.3     setosa\n",
       "19            5.7          3.8           1.7          0.3     setosa\n",
       "20            5.1          3.8           1.5          0.3     setosa\n",
       "21            5.4          3.4           1.7          0.2     setosa\n",
       "22            5.1          3.7           1.5          0.4     setosa\n",
       "23            4.6          3.6           1.0          0.2     setosa\n",
       "24            5.1          3.3           1.7          0.5     setosa\n",
       "25            4.8          3.4           1.9          0.2     setosa\n",
       "26            5.0          3.0           1.6          0.2     setosa\n",
       "27            5.0          3.4           1.6          0.4     setosa\n",
       "28            5.2          3.5           1.5          0.2     setosa\n",
       "29            5.2          3.4           1.4          0.2     setosa\n",
       "30            4.7          3.2           1.6          0.2     setosa\n",
       "..            ...          ...           ...          ...        ...\n",
       "121           6.9          3.2           5.7          2.3  virginica\n",
       "122           5.6          2.8           4.9          2.0  virginica\n",
       "123           7.7          2.8           6.7          2.0  virginica\n",
       "124           6.3          2.7           4.9          1.8  virginica\n",
       "125           6.7          3.3           5.7          2.1  virginica\n",
       "126           7.2          3.2           6.0          1.8  virginica\n",
       "127           6.2          2.8           4.8          1.8  virginica\n",
       "128           6.1          3.0           4.9          1.8  virginica\n",
       "129           6.4          2.8           5.6          2.1  virginica\n",
       "130           7.2          3.0           5.8          1.6  virginica\n",
       "131           7.4          2.8           6.1          1.9  virginica\n",
       "132           7.9          3.8           6.4          2.0  virginica\n",
       "133           6.4          2.8           5.6          2.2  virginica\n",
       "134           6.3          2.8           5.1          1.5  virginica\n",
       "135           6.1          2.6           5.6          1.4  virginica\n",
       "136           7.7          3.0           6.1          2.3  virginica\n",
       "137           6.3          3.4           5.6          2.4  virginica\n",
       "138           6.4          3.1           5.5          1.8  virginica\n",
       "139           6.0          3.0           4.8          1.8  virginica\n",
       "140           6.9          3.1           5.4          2.1  virginica\n",
       "141           6.7          3.1           5.6          2.4  virginica\n",
       "142           6.9          3.1           5.1          2.3  virginica\n",
       "143           5.8          2.7           5.1          1.9  virginica\n",
       "144           6.8          3.2           5.9          2.3  virginica\n",
       "145           6.7          3.3           5.7          2.5  virginica\n",
       "146           6.7          3.0           5.2          2.3  virginica\n",
       "147           6.3          2.5           5.0          1.9  virginica\n",
       "148           6.5          3.0           5.2          2.0  virginica\n",
       "149           6.2          3.4           5.4          2.3  virginica\n",
       "150           5.9          3.0           5.1          1.8  virginica\n",
       "\n",
       "[150 rows x 5 columns]"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# load iris dataset from net\n",
    "# data = datasets.load_iris()\n",
    "# irisDataFrame = pd.DataFrame(data.data, columns=data.feature_names)\n",
    "# load iris from local\n",
    "irisDataFrame = sns.load_dataset('iris',data_home='~/datasets/datasets',cache=True, index_col=0)\n",
    "irisDataFrame"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据内容\n",
    "\n",
    "- sepal_length: 花萼长度\n",
    "- sepal_widht: 花萼宽度\n",
    "- petal_length: 花瓣长度\n",
    "- petal_width: 花瓣宽度\n",
    "- species: 鸢尾花所属的亚种"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(150, 4)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "irisDataFrame.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sepal length (cm)</th>\n",
       "      <th>sepal width (cm)</th>\n",
       "      <th>petal length (cm)</th>\n",
       "      <th>petal width (cm)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>150.000000</td>\n",
       "      <td>150.000000</td>\n",
       "      <td>150.000000</td>\n",
       "      <td>150.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>5.843333</td>\n",
       "      <td>3.054000</td>\n",
       "      <td>3.758667</td>\n",
       "      <td>1.198667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.828066</td>\n",
       "      <td>0.433594</td>\n",
       "      <td>1.764420</td>\n",
       "      <td>0.763161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>4.300000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>5.100000</td>\n",
       "      <td>2.800000</td>\n",
       "      <td>1.600000</td>\n",
       "      <td>0.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>5.800000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>4.350000</td>\n",
       "      <td>1.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.400000</td>\n",
       "      <td>3.300000</td>\n",
       "      <td>5.100000</td>\n",
       "      <td>1.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>7.900000</td>\n",
       "      <td>4.400000</td>\n",
       "      <td>6.900000</td>\n",
       "      <td>2.500000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       sepal length (cm)  sepal width (cm)  petal length (cm)  \\\n",
       "count         150.000000        150.000000         150.000000   \n",
       "mean            5.843333          3.054000           3.758667   \n",
       "std             0.828066          0.433594           1.764420   \n",
       "min             4.300000          2.000000           1.000000   \n",
       "25%             5.100000          2.800000           1.600000   \n",
       "50%             5.800000          3.000000           4.350000   \n",
       "75%             6.400000          3.300000           5.100000   \n",
       "max             7.900000          4.400000           6.900000   \n",
       "\n",
       "       petal width (cm)  \n",
       "count        150.000000  \n",
       "mean           1.198667  \n",
       "std            0.763161  \n",
       "min            0.100000  \n",
       "25%            0.300000  \n",
       "50%            1.300000  \n",
       "75%            1.800000  \n",
       "max            2.500000  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "irisDataFrame.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 150 entries, 0 to 149\n",
      "Data columns (total 4 columns):\n",
      "sepal length (cm)    150 non-null float64\n",
      "sepal width (cm)     150 non-null float64\n",
      "petal length (cm)    150 non-null float64\n",
      "petal width (cm)     150 non-null float64\n",
      "dtypes: float64(4)\n",
      "memory usage: 4.8 KB\n"
     ]
    }
   ],
   "source": [
    "irisDataFrame.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 降维\n",
    "\n",
    "PCA主成分分析鸢尾花数据集合"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<iframe src=\"http://192.168.0.72:32770/\"></iframe>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f05fb58f1d0>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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bN25USEiIAyrj1CQAAMiHiIgI0yXYzc/PTx9//HG+Xuvr66uwsLACrui/mBEDAAAwhCAG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\nghgAAIAh/w/s62x5XTNcBwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f05fc0d2fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "irisDataFrame.plot(kind='hist')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7f05fb4f7898>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f05fb384860>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x7f05fb398e10>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x7f05fb2cbb70>]], dtype=object)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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nnlBkZKQ3cwGAadDeASiPR8XU119/rV9//VXp6enavXu3Jk2apKVLl3o7GwD4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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f05fb52c8d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "irisDataFrame.hist(bins=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['T',\n",
       " '_AXIS_ALIASES',\n",
       " '_AXIS_IALIASES',\n",
       " '_AXIS_LEN',\n",
       " '_AXIS_NAMES',\n",
       " '_AXIS_NUMBERS',\n",
       " '_AXIS_ORDERS',\n",
       " '_AXIS_REVERSED',\n",
       " '_AXIS_SLICEMAP',\n",
       " '__abs__',\n",
       " '__add__',\n",
       " '__and__',\n",
       " '__array__',\n",
       " '__array_wrap__',\n",
       " '__bool__',\n",
       " '__bytes__',\n",
       " '__class__',\n",
       " '__contains__',\n",
       " '__delattr__',\n",
       " '__delitem__',\n",
       " '__dict__',\n",
       " '__dir__',\n",
       " '__div__',\n",
       " '__doc__',\n",
       " '__eq__',\n",
       " '__finalize__',\n",
       " '__floordiv__',\n",
       " '__format__',\n",
       " '__ge__',\n",
       " '__getattr__',\n",
       " '__getattribute__',\n",
       " '__getitem__',\n",
       " '__getstate__',\n",
       " '__gt__',\n",
       " '__hash__',\n",
       " '__iadd__',\n",
       " '__imul__',\n",
       " '__init__',\n",
       " '__init_subclass__',\n",
       " '__invert__',\n",
       " '__ipow__',\n",
       " '__isub__',\n",
       " '__iter__',\n",
       " '__itruediv__',\n",
       " '__le__',\n",
       " '__len__',\n",
       " '__lt__',\n",
       " '__mod__',\n",
       " '__module__',\n",
       " '__mul__',\n",
       " '__ne__',\n",
       " '__neg__',\n",
       " '__new__',\n",
       " '__nonzero__',\n",
       " '__or__',\n",
       " '__pow__',\n",
       " '__radd__',\n",
       " '__rand__',\n",
       " '__rdiv__',\n",
       " '__reduce__',\n",
       " '__reduce_ex__',\n",
       " '__repr__',\n",
       " '__rfloordiv__',\n",
       " '__rmod__',\n",
       " '__rmul__',\n",
       " '__ror__',\n",
       " '__round__',\n",
       " '__rpow__',\n",
       " '__rsub__',\n",
       " '__rtruediv__',\n",
       " '__rxor__',\n",
       " '__setattr__',\n",
       " '__setitem__',\n",
       " '__setstate__',\n",
       " '__sizeof__',\n",
       " '__str__',\n",
       " '__sub__',\n",
       " '__subclasshook__',\n",
       " '__truediv__',\n",
       " '__unicode__',\n",
       " '__weakref__',\n",
       " '__xor__',\n",
       " '_accessors',\n",
       " '_add_numeric_operations',\n",
       " '_add_series_only_operations',\n",
       " '_add_series_or_dataframe_operations',\n",
       " '_agg_by_level',\n",
       " '_align_frame',\n",
       " '_align_series',\n",
       " '_apply_broadcast',\n",
       " '_apply_empty_result',\n",
       " '_apply_raw',\n",
       " '_apply_standard',\n",
       " '_at',\n",
       " '_box_col_values',\n",
       " '_box_item_values',\n",
       " '_check_inplace_setting',\n",
       " '_check_is_chained_assignment_possible',\n",
       " '_check_percentile',\n",
       " '_check_setitem_copy',\n",
       " '_clear_item_cache',\n",
       " '_combine_const',\n",
       " '_combine_frame',\n",
       " '_combine_match_columns',\n",
       " '_combine_match_index',\n",
       " '_combine_series',\n",
       " '_combine_series_infer',\n",
       " '_compare_frame',\n",
       " '_compare_frame_evaluate',\n",
       " '_consolidate_inplace',\n",
       " '_construct_axes_dict',\n",
       " '_construct_axes_dict_for_slice',\n",
       " '_construct_axes_dict_from',\n",
       " '_construct_axes_from_arguments',\n",
       " '_constructor',\n",
       " '_constructor_expanddim',\n",
       " '_constructor_sliced',\n",
       " '_convert',\n",
       " '_count_level',\n",
       " '_create_indexer',\n",
       " '_dir_additions',\n",
       " '_dir_deletions',\n",
       " '_ensure_valid_index',\n",
       " '_expand_axes',\n",
       " '_flex_compare_frame',\n",
       " '_from_arrays',\n",
       " '_from_axes',\n",
       " '_get_agg_axis',\n",
       " '_get_axis',\n",
       " '_get_axis_name',\n",
       " '_get_axis_number',\n",
       " '_get_axis_resolvers',\n",
       " '_get_block_manager_axis',\n",
       " '_get_bool_data',\n",
       " '_get_cacher',\n",
       " '_get_index_resolvers',\n",
       " '_get_item_cache',\n",
       " '_get_numeric_data',\n",
       " '_get_values',\n",
       " '_getitem_array',\n",
       " '_getitem_column',\n",
       " '_getitem_frame',\n",
       " '_getitem_multilevel',\n",
       " '_getitem_slice',\n",
       " '_iat',\n",
       " '_iget_item_cache',\n",
       " '_iloc',\n",
       " '_indexed_same',\n",
       " '_info_axis',\n",
       " '_info_axis_name',\n",
       " '_info_axis_number',\n",
       " '_info_repr',\n",
       " '_init_dict',\n",
       " '_init_mgr',\n",
       " '_init_ndarray',\n",
       " '_internal_names',\n",
       " '_internal_names_set',\n",
       " '_is_cached',\n",
       " '_is_datelike_mixed_type',\n",
       " '_is_mixed_type',\n",
       " '_is_numeric_mixed_type',\n",
       " '_is_view',\n",
       " '_ix',\n",
       " '_ixs',\n",
       " '_join_compat',\n",
       " '_loc',\n",
       " '_maybe_cache_changed',\n",
       " '_maybe_update_cacher',\n",
       " '_metadata',\n",
       " '_needs_reindex_multi',\n",
       " '_protect_consolidate',\n",
       " '_reduce',\n",
       " '_reindex_axes',\n",
       " '_reindex_axis',\n",
       " '_reindex_columns',\n",
       " '_reindex_index',\n",
       " '_reindex_multi',\n",
       " '_reindex_with_indexers',\n",
       " '_repr_fits_horizontal_',\n",
       " '_repr_fits_vertical_',\n",
       " '_repr_html_',\n",
       " '_repr_latex_',\n",
       " '_reset_cache',\n",
       " '_reset_cacher',\n",
       " '_sanitize_column',\n",
       " '_series',\n",
       " '_set_as_cached',\n",
       " '_set_axis',\n",
       " '_set_axis_name',\n",
       " '_set_is_copy',\n",
       " '_set_item',\n",
       " '_setitem_array',\n",
       " '_setitem_frame',\n",
       " '_setitem_slice',\n",
       " '_setup_axes',\n",
       " '_slice',\n",
       " '_stat_axis',\n",
       " '_stat_axis_name',\n",
       " '_stat_axis_number',\n",
       " '_typ',\n",
       " '_unpickle_frame_compat',\n",
       " '_unpickle_matrix_compat',\n",
       " '_update_inplace',\n",
       " '_validate_dtype',\n",
       " '_values',\n",
       " '_where',\n",
       " '_xs',\n",
       " 'abs',\n",
       " 'add',\n",
       " 'add_prefix',\n",
       " 'add_suffix',\n",
       " 'align',\n",
       " 'all',\n",
       " 'any',\n",
       " 'append',\n",
       " 'apply',\n",
       " 'applymap',\n",
       " 'as_blocks',\n",
       " 'as_matrix',\n",
       " 'asfreq',\n",
       " 'asof',\n",
       " 'assign',\n",
       " 'astype',\n",
       " 'at',\n",
       " 'at_time',\n",
       " 'axes',\n",
       " 'between_time',\n",
       " 'bfill',\n",
       " 'blocks',\n",
       " 'bool',\n",
       " 'boxplot',\n",
       " 'clip',\n",
       " 'clip_lower',\n",
       " 'clip_upper',\n",
       " 'columns',\n",
       " 'combine',\n",
       " 'combineAdd',\n",
       " 'combineMult',\n",
       " 'combine_first',\n",
       " 'compound',\n",
       " 'consolidate',\n",
       " 'convert_objects',\n",
       " 'copy',\n",
       " 'corr',\n",
       " 'corrwith',\n",
       " 'count',\n",
       " 'cov',\n",
       " 'cummax',\n",
       " 'cummin',\n",
       " 'cumprod',\n",
       " 'cumsum',\n",
       " 'describe',\n",
       " 'diff',\n",
       " 'div',\n",
       " 'divide',\n",
       " 'dot',\n",
       " 'drop',\n",
       " 'drop_duplicates',\n",
       " 'dropna',\n",
       " 'dtypes',\n",
       " 'duplicated',\n",
       " 'empty',\n",
       " 'eq',\n",
       " 'equals',\n",
       " 'eval',\n",
       " 'ewm',\n",
       " 'expanding',\n",
       " 'ffill',\n",
       " 'fillna',\n",
       " 'filter',\n",
       " 'first',\n",
       " 'first_valid_index',\n",
       " 'floordiv',\n",
       " 'from_csv',\n",
       " 'from_dict',\n",
       " 'from_items',\n",
       " 'from_records',\n",
       " 'ftypes',\n",
       " 'ge',\n",
       " 'get',\n",
       " 'get_dtype_counts',\n",
       " 'get_ftype_counts',\n",
       " 'get_value',\n",
       " 'get_values',\n",
       " 'groupby',\n",
       " 'gt',\n",
       " 'head',\n",
       " 'hist',\n",
       " 'iat',\n",
       " 'icol',\n",
       " 'idxmax',\n",
       " 'idxmin',\n",
       " 'iget_value',\n",
       " 'iloc',\n",
       " 'index',\n",
       " 'info',\n",
       " 'insert',\n",
       " 'interpolate',\n",
       " 'irow',\n",
       " 'is_copy',\n",
       " 'isin',\n",
       " 'isnull',\n",
       " 'items',\n",
       " 'iteritems',\n",
       " 'iterkv',\n",
       " 'iterrows',\n",
       " 'itertuples',\n",
       " 'ix',\n",
       " 'join',\n",
       " 'keys',\n",
       " 'kurt',\n",
       " 'kurtosis',\n",
       " 'last',\n",
       " 'last_valid_index',\n",
       " 'le',\n",
       " 'loc',\n",
       " 'lookup',\n",
       " 'lt',\n",
       " 'mad',\n",
       " 'mask',\n",
       " 'max',\n",
       " 'mean',\n",
       " 'median',\n",
       " 'memory_usage',\n",
       " 'merge',\n",
       " 'min',\n",
       " 'mod',\n",
       " 'mode',\n",
       " 'mul',\n",
       " 'multiply',\n",
       " 'ndim',\n",
       " 'ne',\n",
       " 'nlargest',\n",
       " 'notnull',\n",
       " 'nsmallest',\n",
       " 'pct_change',\n",
       " 'pipe',\n",
       " 'pivot',\n",
       " 'pivot_table',\n",
       " 'plot',\n",
       " 'pop',\n",
       " 'pow',\n",
       " 'prod',\n",
       " 'product',\n",
       " 'quantile',\n",
       " 'query',\n",
       " 'radd',\n",
       " 'rank',\n",
       " 'rdiv',\n",
       " 'reindex',\n",
       " 'reindex_axis',\n",
       " 'reindex_like',\n",
       " 'rename',\n",
       " 'rename_axis',\n",
       " 'reorder_levels',\n",
       " 'replace',\n",
       " 'resample',\n",
       " 'reset_index',\n",
       " 'rfloordiv',\n",
       " 'rmod',\n",
       " 'rmul',\n",
       " 'rolling',\n",
       " 'round',\n",
       " 'rpow',\n",
       " 'rsub',\n",
       " 'rtruediv',\n",
       " 'sample',\n",
       " 'select',\n",
       " 'select_dtypes',\n",
       " 'sem',\n",
       " 'set_axis',\n",
       " 'set_index',\n",
       " 'set_value',\n",
       " 'shape',\n",
       " 'shift',\n",
       " 'size',\n",
       " 'skew',\n",
       " 'slice_shift',\n",
       " 'sort',\n",
       " 'sort_index',\n",
       " 'sort_values',\n",
       " 'sortlevel',\n",
       " 'squeeze',\n",
       " 'stack',\n",
       " 'std',\n",
       " 'style',\n",
       " 'sub',\n",
       " 'subtract',\n",
       " 'sum',\n",
       " 'swapaxes',\n",
       " 'swaplevel',\n",
       " 'tail',\n",
       " 'take',\n",
       " 'to_clipboard',\n",
       " 'to_csv',\n",
       " 'to_dense',\n",
       " 'to_dict',\n",
       " 'to_excel',\n",
       " 'to_gbq',\n",
       " 'to_hdf',\n",
       " 'to_html',\n",
       " 'to_json',\n",
       " 'to_latex',\n",
       " 'to_msgpack',\n",
       " 'to_panel',\n",
       " 'to_period',\n",
       " 'to_pickle',\n",
       " 'to_records',\n",
       " 'to_sparse',\n",
       " 'to_sql',\n",
       " 'to_stata',\n",
       " 'to_string',\n",
       " 'to_timestamp',\n",
       " 'to_xarray',\n",
       " 'transpose',\n",
       " 'truediv',\n",
       " 'truncate',\n",
       " 'tshift',\n",
       " 'tz_convert',\n",
       " 'tz_localize',\n",
       " 'unstack',\n",
       " 'update',\n",
       " 'values',\n",
       " 'var',\n",
       " 'where',\n",
       " 'xs']"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dir(irisDataFrame)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method NDFrame.head of      Unnamed: 0  Sepal.Length  Sepal.Width  Petal.Length  Petal.Width  \\\n",
       "0             1           5.1          3.5           1.4          0.2   \n",
       "1             2           4.9          3.0           1.4          0.2   \n",
       "2             3           4.7          3.2           1.3          0.2   \n",
       "3             4           4.6          3.1           1.5          0.2   \n",
       "4             5           5.0          3.6           1.4          0.2   \n",
       "5             6           5.4          3.9           1.7          0.4   \n",
       "6             7           4.6          3.4           1.4          0.3   \n",
       "7             8           5.0          3.4           1.5          0.2   \n",
       "8             9           4.4          2.9           1.4          0.2   \n",
       "9            10           4.9          3.1           1.5          0.1   \n",
       "10           11           5.4          3.7           1.5          0.2   \n",
       "11           12           4.8          3.4           1.6          0.2   \n",
       "12           13           4.8          3.0           1.4          0.1   \n",
       "13           14           4.3          3.0           1.1          0.1   \n",
       "14           15           5.8          4.0           1.2          0.2   \n",
       "15           16           5.7          4.4           1.5          0.4   \n",
       "16           17           5.4          3.9           1.3          0.4   \n",
       "17           18           5.1          3.5           1.4          0.3   \n",
       "18           19           5.7          3.8           1.7          0.3   \n",
       "19           20           5.1          3.8           1.5          0.3   \n",
       "20           21           5.4          3.4           1.7          0.2   \n",
       "21           22           5.1          3.7           1.5          0.4   \n",
       "22           23           4.6          3.6           1.0          0.2   \n",
       "23           24           5.1          3.3           1.7          0.5   \n",
       "24           25           4.8          3.4           1.9          0.2   \n",
       "25           26           5.0          3.0           1.6          0.2   \n",
       "26           27           5.0          3.4           1.6          0.4   \n",
       "27           28           5.2          3.5           1.5          0.2   \n",
       "28           29           5.2          3.4           1.4          0.2   \n",
       "29           30           4.7          3.2           1.6          0.2   \n",
       "..          ...           ...          ...           ...          ...   \n",
       "120         121           6.9          3.2           5.7          2.3   \n",
       "121         122           5.6          2.8           4.9          2.0   \n",
       "122         123           7.7          2.8           6.7          2.0   \n",
       "123         124           6.3          2.7           4.9          1.8   \n",
       "124         125           6.7          3.3           5.7          2.1   \n",
       "125         126           7.2          3.2           6.0          1.8   \n",
       "126         127           6.2          2.8           4.8          1.8   \n",
       "127         128           6.1          3.0           4.9          1.8   \n",
       "128         129           6.4          2.8           5.6          2.1   \n",
       "129         130           7.2          3.0           5.8          1.6   \n",
       "130         131           7.4          2.8           6.1          1.9   \n",
       "131         132           7.9          3.8           6.4          2.0   \n",
       "132         133           6.4          2.8           5.6          2.2   \n",
       "133         134           6.3          2.8           5.1          1.5   \n",
       "134         135           6.1          2.6           5.6          1.4   \n",
       "135         136           7.7          3.0           6.1          2.3   \n",
       "136         137           6.3          3.4           5.6          2.4   \n",
       "137         138           6.4          3.1           5.5          1.8   \n",
       "138         139           6.0          3.0           4.8          1.8   \n",
       "139         140           6.9          3.1           5.4          2.1   \n",
       "140         141           6.7          3.1           5.6          2.4   \n",
       "141         142           6.9          3.1           5.1          2.3   \n",
       "142         143           5.8          2.7           5.1          1.9   \n",
       "143         144           6.8          3.2           5.9          2.3   \n",
       "144         145           6.7          3.3           5.7          2.5   \n",
       "145         146           6.7          3.0           5.2          2.3   \n",
       "146         147           6.3          2.5           5.0          1.9   \n",
       "147         148           6.5          3.0           5.2          2.0   \n",
       "148         149           6.2          3.4           5.4          2.3   \n",
       "149         150           5.9          3.0           5.1          1.8   \n",
       "\n",
       "       Species  \n",
       "0       setosa  \n",
       "1       setosa  \n",
       "2       setosa  \n",
       "3       setosa  \n",
       "4       setosa  \n",
       "5       setosa  \n",
       "6       setosa  \n",
       "7       setosa  \n",
       "8       setosa  \n",
       "9       setosa  \n",
       "10      setosa  \n",
       "11      setosa  \n",
       "12      setosa  \n",
       "13      setosa  \n",
       "14      setosa  \n",
       "15      setosa  \n",
       "16      setosa  \n",
       "17      setosa  \n",
       "18      setosa  \n",
       "19      setosa  \n",
       "20      setosa  \n",
       "21      setosa  \n",
       "22      setosa  \n",
       "23      setosa  \n",
       "24      setosa  \n",
       "25      setosa  \n",
       "26      setosa  \n",
       "27      setosa  \n",
       "28      setosa  \n",
       "29      setosa  \n",
       "..         ...  \n",
       "120  virginica  \n",
       "121  virginica  \n",
       "122  virginica  \n",
       "123  virginica  \n",
       "124  virginica  \n",
       "125  virginica  \n",
       "126  virginica  \n",
       "127  virginica  \n",
       "128  virginica  \n",
       "129  virginica  \n",
       "130  virginica  \n",
       "131  virginica  \n",
       "132  virginica  \n",
       "133  virginica  \n",
       "134  virginica  \n",
       "135  virginica  \n",
       "136  virginica  \n",
       "137  virginica  \n",
       "138  virginica  \n",
       "139  virginica  \n",
       "140  virginica  \n",
       "141  virginica  \n",
       "142  virginica  \n",
       "143  virginica  \n",
       "144  virginica  \n",
       "145  virginica  \n",
       "146  virginica  \n",
       "147  virginica  \n",
       "148  virginica  \n",
       "149  virginica  \n",
       "\n",
       "[150 rows x 6 columns]>"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "irisDataFrame.head"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['setosa', 'versicolor', 'virginica'], dtype=object)"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "irisDataFrame['Species'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1.4,  1.3,  1.5,  1.7,  1.6,  1.1,  1.2,  1. ,  1.9,  4.7,  4.5,\n",
       "        4.9,  4. ,  4.6,  3.3,  3.9,  3.5,  4.2,  3.6,  4.4,  4.1,  4.8,\n",
       "        4.3,  5. ,  3.8,  3.7,  5.1,  3. ,  6. ,  5.9,  5.6,  5.8,  6.6,\n",
       "        6.3,  6.1,  5.3,  5.5,  6.7,  6.9,  5.7,  6.4,  5.4,  5.2])"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "irisDataFrame['Petal.Length'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f05f5285c88>"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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yuK+ZC3SmajNJhBBVqhpTuU13lXG/2y08SMoWXEgpMZIttwymwtD+RVK2fg+l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i5/RMio6cHVdTYZJdgedDCaidxRPuWmA7aJ+/I1nh94nnHdPp0kyLhEt7P59+2I4NMC3xBAPlJb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\n4CCJYRiGYRgmBw6SGIZhGIZhcvj/hLNn0TSa13AAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f05f5393940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "irisDataFrame.plot.area(stacked=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x7f05eef3f358>"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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QB0dZ6dnAPpRYXAjTC3+82i8NM31Gtb0Sht/9L3I+ezNML73COSbt2hqM221L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\nERGRarjAICIiIiIi1XCBQUREREREqvkBnbcdlMixRIEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f05ee44ce48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(irisDataFrame, hue=\"Species\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f05edea36d8>"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Z+SKi+MPwRUQB8x2qHbSeL1a+iCh+MHwRUcB8DffB2nZk5YuI4gjDFxEFzMSG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\nXejQtg4H6r2U2HL8JUmSiL9sEfGXLcJU38Deu+7F1DS26p9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6AB0/7KjCbPG8bv6C8kTy\nJQyL0UOSL0tnJ8UrVyFpNKQtvgFJ7Xrz9xIv/wO+iQnUffU1rdt3HPOxVW32/kSxgUNLvgCi4+0t\nNTxx9avk1Tforakh+vxzCZ46BYBwv1B8NN4O33bsMVkoqGglLVbvMf29BsNw0lxif3sBvbV15D/x\nlFuPIFKrVSyYFkdHt5kNe0TPL8HxRPIlDEtLcxdIuP1Q7dLX/0FfSwtxl1yEb3y80uEckcrLi/Ql\ni5HUaopeWInc23vUx1a1DyRfkUO+T0x/3Ve1h9V9Na77iYbv1uCXkkLC7y/b/3GVpCJBH0N1Rx19\nFset9uWWNmO1yR5f73Uk8Zct2j+CqOztd5QOZ0ROn50AwJcbyhSNQ/BMIvkShsXY3E1gkDcajeut\nFA1W6/YdNKz5Hr/kJGIuOF/pcI7JLymRuEsuoq+5BcvX3x71cQPbjtHDSL6iPbDTfW99PcUvrULl\n7U3G0iWHjYhK1MchyzIVbY6b57e/3stDW0wci6RWk37LTfjERFPz8acjmtSgtGiDP5PTDOwtbqai\nzvNbsAijSyRfwpCZzVba23rdutje1tdHyarXQKUibfFfHT7TzxliLvwNfinJWHfupmXrtiM+pqq9\nFoNfKN6aoY9DCgj0JiDIm5oKo0ccsbcNHFTo7ibl2mvwiY4+7DH7674cuPW4u6gRjVoiKynEYdd0\nJxo/P7LuXIbaz5eiF1/GVu2+g6pPPyERgK82lisbiOBxRPIlDFlLk/2kY1i4v8KRDF/Vhx/TW1dH\n9Dln4ZeUqHQ4g6LSaEhb/FdQqSh64aXDipo7TV0Ye9uHVe81ICZeT2eHiY62o29tuovKf/2bjvwC\nwuadhGHByUd8TKI+FoCyVsecauvs7qO4uo2MhBC8vVw/oXcWn5hoMpbegmy10vfv9+lraVU6pGGZ\nlR1JSKCONVsq6DWNjekPwugQyZcwZC2N9jf9EIN7rnz11NZS9f6HeIWEELfoEqXDGRK/xAQ0J5+E\nubWVktfePORzVQMnHYex5Tgg2kPqvoy791D1/ofoIsJJuf7PR53CEBsUhVpSOWzla09xE7IME8dA\ni4njCZ46hYQ//A46Osl79AlsZrPSIQ2ZRq3i17MS6eq1sEZ0vBccSCRfwpA1NdhXvkIN7rfyJcsy\nJateQzabSbr6SjS+7ndgQD13Dn4pKTR+v5bmTQeaWlb3F9vHjGDl60Dy5Z4rFQDm9nYKn34OSaUi\n49ab0fge/USul1pLTGAU5W3V2OShjXE6ku35jQBMSR/cUHNPF/Ob81CNz6YjP5/il19xy+3sM09I\nRKNW8fHaYqw294tfcE0i+RKGbGDlK9QNV76aN2zEuGMn+smTCD1hjtLhDIukUpG+5K9IGg3FL72M\nucM+HscRK18x8XqQoKrcPZMvWZYpen4lfS0txF+2iICM9OM+J1Efi8liwmge2ZghWZbZnlePn4+W\n9P7DC2OdJElozzkTv5QUGr5dQ+0XXyod0pAFB3qzcHoctc1dbNwr2k4IjiGSL2HImhu7UKkktxst\nZOnuofS1N5A0GpKvvdqtB4L7xscTf+klmFuNlL72BnBwm4nhr3zpvLVERAZSU2HEahn5StBoq/3i\nS1o2byFo4oRBn2BNDLbXfdWbmkd07+rGThpae5icZkCtFj9aB0haLVnLb0er11P6+psYd+9ROqQh\n+838FCQJPvq+yC1X7wTXI35CCEPW3NhJcKiv273BVK7+N33NLcRe+JsjnnxzNzG/OQ//tFQa166j\nedMWqtvrCPHR4+s1sq3UuKRgLBYbdTVtDop0dHQWl1D25ltogwJJv/kmJNXgXp8DRfcNfSNLvrbn\nNwAwJUNsOf6SLiyUzDtuQ1KpyH/8SXrr65UOaUhiwwOYOS6S/IpWckpG9joRBBDJlzBE3V199HSb\nCXGzeq+u8gpqPv0c78gIYi78jdLhOISkVpO22L79WLTyZTpam4gZwZbjgNhEe4uEytKWEV9rtFi6\ne8h/4u/944MW4xUSPOjnJurt7SZGuvK1o7/ea6pIvo4oMCuT5GuvxtLRyb6HH8Xa06N0SEPy24Vp\nALz3db7CkQieQCRfwpAMtJlwp3ovWZYpefkVsNlI/vPVqHVD74Hlqnzj44i/9BIsRiPzt3WMaMtx\nQNxA8lXmHnVfsixT/NLL9NbWEXPB+fvHBw2Wv84Pg18odb1Nw95SMlus7CluIi7CH4ObT31wpshf\n/4rIM0+nu7yCgmeeR7a5z9Z2ZmII0zLD2V3UxK6CRqXDEdycSL6EIWl2w2L7xrU/0J67j5DZswie\nNlXpcBwu5jfnYYuPJLPMREJl94ivpw/xwT9AR2VZi1vUtzR8+x1N634iICOD+N9dOqxrpIUm0WPr\npb5zeG+quSUtmPqsTM2IGNbzx5Kkq64kcHw2LRs3Ufnv95UOZ0h+f0YWAG9/mesW3xuC6xLJlzAk\nzY32lS932Xa0dHVR9o//Q+XlRfLVVyodjlNIajWVZ0/GogKfD9buP/047OtJEnFJIXS2m2hrde2t\noe6KCkpeeR21nx/pS5cMe1JBemgSAAXNpcN6/rb+ei+x5Xh8Ko2GzNuXogs3UPneapo3blI6pEFL\njdUzd2I0BRVGNuXUKR2O4MZE8iUMSVO9/Y09zE2Sr4r3VmM2Gom96EJ0BoPS4ThNoVcnmyb6Y2vr\noPTVN0Z8vbhEe82UK9d9WU0m8p94CltfH2k3/gXv8OEnPmn7k6+SYT1/W149XhoV2Smhw45hLNEG\nBpK1/A5UOh0FTz9HV3mF0iEN2u9Oz0SlknjzsxzMFqvS4QhuSiRfwpA01nXg7aPFP9D166a6ysqp\n/eJLvKMiifnNeUqH4zSyLFNurKZmegL+aWk0/rCO5k2bR3TN/UX3Za6ZfMmyTNELL9FdUUnUWWcQ\nOmf2iK6XpI9DLakpHMbKV11zFxV1HUxKN6DTuu+g+dHml5RI2k03YuvtZd/Dj2BuH9mK7WiJiwjg\nrLlJ1DR18fEPxUqHI7gpkXwJg2YxW2lp6iI8KsDle2TZO9m/ur/IXqXVKh2S07T2tNHZ10VcSCxp\nN/0VSauleOWqEb2ZRcUEodGoXLbovvbz/9K07kcCMtJJvPLyEV9Po9YQoQul3FiNydI3pOdu7t9+\nmpU98pOmY03Y3DnEXvxbTPUN5D3yGLa+oX3tlXLZaZkE+Xux+tsCGl18a15wTSL5EgatqaETWQZD\nRIDSoRxX4w/r7EX2s2YO+fSbuylvs88lTNDH4BsXS/xlizAbjZS8+vqwr6nWqIiO19NQ246p17Vm\n8rXl5Pb38woi4/alDkuso3Xh2GQbxS3lQ3reQO3PjHEi+RqO+EsvIezEubTn7qPwuRfc4gSkv4+W\nK84ah6nPyovv7xTF98KQieRLGLTGOvtKiiHStZMvS3c3Zf94G5WXF0lXeWaR/cHKjdUAxAfFABBz\n3jn4p6fRtO5HGn9cP+zrxiWGIMuu1XLC1NxC/uN/R5ZlMv52K7pQx9VYxfjYa8aGsvXY2d3H3pJm\n0uP1hAR6OyyWsURSqUi76a8EZGbQ9ON6Kt59T+mQBuWUGfFMTjewLa+BrzcNLWEXBJF8CYPW0J98\nhbt48lX53mrMrfYie+8Izz99Vm60r3wNdGqX1GrSlyxG5e1N8cqXh91NPKG/eLy82DU6etvMZvIf\nexKz0UjSlZcTND7bodeP1tlfK/lNg6/j2ZbXgM0mM1NsOY6IysuLrDvvwDsqkqr3P6T+m2+VDum4\nJEnipkum4Oet4fVP91Lb3wNREAZDJF/CoLnDyldXeQU1n/8X78hIYs4/V+lwRkWFsRofjTdhfiH7\nP+YTE03KtVdj7e6m4O/PYLNYhnzd+KQQVCqJsqImR4Y7LLIsU7zyZTry8wk7aS5R55zl8HsEav2J\n8Asjt7EQ2yC3vg7Ue428ue1Ypw0MZNw9d6IJCKBo5SqMO3cpHdJxhel9uO6CifSYrDzy1mZ6+4b+\nfSaMTSL5Egatoa4DP38v/Pxd86TjoUX2V6Hy8lI6JKczW81Ud9QTHxSNSjr029mwYD5h806iI7+A\nyn/9e8jX9tJpiI7TU1PVhqlX2TeVqvc/pGHNWvzTUkm98QanHfjIDk+n29xDmbHyuI81W2xsy6sn\nPMSXBBf+hcSd+ERHk7X8diSVirzHnqSrzPW38+ZPi+P0OYmU1rSz8v1dov5LGBSRfAmD0meyYGzp\ndulVr6Z1P9Gek0vIrBke2cn+SCraarDJNhL6txwPJkkSKdf/GV1EOFXvf4hx954hXz8xNRTZJlNR\nqtzWY+OP66l455/oDGFk3XmHU8dDjY/IAGBvw/Hn9+0tbqKr18LMcREuf/rXnQSOyyLtphuxdneT\n+8DDmBpdf5TPn88fT0Z8MN9vq+Lf3xYoHY7gBkTyJQxKY719rJCrnnQ0d3RQ+vqbY6bIfsDAybyU\nkIQjfl7j60vGrTcjqVQUPPk0pqahJVGJqWEAlBUpk3x15BdQ+OzzqH18yLprOV7Bgx+YPRzZ4fbk\nK6fh+G+gP+2qAWDuxGinxjQWGeadSMLlf6CvuZmcex/A3NamdEjHpNWoWXbFDMJDfHnnqzy+3FCm\ndEiCixPJlzAo9TX2H34R0YEKR3Jk5W+9g7mtjbhLL8E7YuzM1zte8gXYe2H96QrMbW3kPfr4kHop\nxSUGo1IrU/fVXVFJ7oMrkK1WMm67Bb/Eo/8dHSXYJ4iYgEhyG4uw2I7evdxitbFhTw0hgTqykkRX\ne2eIveB8os8/l57qGnIfeBhLt2v30woN8uGBP88h0M+Llz/Yxffbjr91LYxdIvkSBqW2yp58RcXq\nFY7kcG05OdR/8y2+iQlEn3u20uGMqpKWcrzUWmICj33aLuqsMwhfOJ/OwiKKX1o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9AAAX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\nfImIiIgk0P8D65HESdlISHAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f05ef41ba58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "irisDataFrame.plot(kind='kde')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f05ef49c208>"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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T6VS1atU0adIkJSYmKjs7W/PmzVNZWZnq1q171XuqVaums2fPql+/fvL391dBQcEN7TMr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\nxAAAAAz5fzE6favsBe6eAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f05ef57d400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "irisDataFrame.plot(kind='hist')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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PfvADffvb39a0adO6N7fDniL/4I77wp0kDtIGiQ8mfrx/kGEV0nJfNUcN71/o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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f05ef696710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 取出所有为setosa的鸢尾花数据\n",
    "setosa = irisDataFrame.loc[irisDataFrame.Species == 'setosa']\n",
    "\n",
    "# 取出所有为virginica的鸢尾花数据\n",
    "virginica = irisDataFrame.loc[irisDataFrame.Species == 'virginica']\n",
    "\n",
    "# 取出所有为versicolor的鸢尾花数据\n",
    "versicolor = irisDataFrame.loc[irisDataFrame.Species == 'versicolor']\n",
    "\n",
    "# 分别绘制setosa和virginica两种鸢尾花的花萼宽度，花萼长度两个维度的KDE可视化\n",
    "ax = sns.kdeplot(setosa['Sepal.Width'], setosa['Sepal.Length'], cmap=\"Reds\", shade=True, shade_lowest=False)\n",
    "ax = sns.kdeplot(virginica['Sepal.Width'], virginica['Sepal.Length'], cmap=\"Blues\", shade=True, shade_lowest=False)\n",
    "# ax = sns.kdeplot(versicolor['Sepal.Width'], versicolor['Sepal.Length'], cmap=\"Greens\", shade=True, shade_lowest=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method NDFrame.head of     Sepal.Length  Sepal.Width  Petal.Length  Petal.Width Species\n",
       "1            5.1          3.5           1.4          0.2  setosa\n",
       "2            4.9          3.0           1.4          0.2  setosa\n",
       "3            4.7          3.2           1.3          0.2  setosa\n",
       "4            4.6          3.1           1.5          0.2  setosa\n",
       "5            5.0          3.6           1.4          0.2  setosa\n",
       "6            5.4          3.9           1.7          0.4  setosa\n",
       "7            4.6          3.4           1.4          0.3  setosa\n",
       "8            5.0          3.4           1.5          0.2  setosa\n",
       "9            4.4          2.9           1.4          0.2  setosa\n",
       "10           4.9          3.1           1.5          0.1  setosa\n",
       "11           5.4          3.7           1.5          0.2  setosa\n",
       "12           4.8          3.4           1.6          0.2  setosa\n",
       "13           4.8          3.0           1.4          0.1  setosa\n",
       "14           4.3          3.0           1.1          0.1  setosa\n",
       "15           5.8          4.0           1.2          0.2  setosa\n",
       "16           5.7          4.4           1.5          0.4  setosa\n",
       "17           5.4          3.9           1.3          0.4  setosa\n",
       "18           5.1          3.5           1.4          0.3  setosa\n",
       "19           5.7          3.8           1.7          0.3  setosa\n",
       "20           5.1          3.8           1.5          0.3  setosa\n",
       "21           5.4          3.4           1.7          0.2  setosa\n",
       "22           5.1          3.7           1.5          0.4  setosa\n",
       "23           4.6          3.6           1.0          0.2  setosa\n",
       "24           5.1          3.3           1.7          0.5  setosa\n",
       "25           4.8          3.4           1.9          0.2  setosa\n",
       "26           5.0          3.0           1.6          0.2  setosa\n",
       "27           5.0          3.4           1.6          0.4  setosa\n",
       "28           5.2          3.5           1.5          0.2  setosa\n",
       "29           5.2          3.4           1.4          0.2  setosa\n",
       "30           4.7          3.2           1.6          0.2  setosa\n",
       "31           4.8          3.1           1.6          0.2  setosa\n",
       "32           5.4          3.4           1.5          0.4  setosa\n",
       "33           5.2          4.1           1.5          0.1  setosa\n",
       "34           5.5          4.2           1.4          0.2  setosa\n",
       "35           4.9          3.1           1.5          0.2  setosa\n",
       "36           5.0          3.2           1.2          0.2  setosa\n",
       "37           5.5          3.5           1.3          0.2  setosa\n",
       "38           4.9          3.6           1.4          0.1  setosa\n",
       "39           4.4          3.0           1.3          0.2  setosa\n",
       "40           5.1          3.4           1.5          0.2  setosa\n",
       "41           5.0          3.5           1.3          0.3  setosa\n",
       "42           4.5          2.3           1.3          0.3  setosa\n",
       "43           4.4          3.2           1.3          0.2  setosa\n",
       "44           5.0          3.5           1.6          0.6  setosa\n",
       "45           5.1          3.8           1.9          0.4  setosa\n",
       "46           4.8          3.0           1.4          0.3  setosa\n",
       "47           5.1          3.8           1.6          0.2  setosa\n",
       "48           4.6          3.2           1.4          0.2  setosa\n",
       "49           5.3          3.7           1.5          0.2  setosa\n",
       "50           5.0          3.3           1.4          0.2  setosa>"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "setosa.head"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sepal.Length</th>\n",
       "      <th>Sepal.Width</th>\n",
       "      <th>Petal.Length</th>\n",
       "      <th>Petal.Width</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Sepal.Length</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.117570</td>\n",
       "      <td>0.871754</td>\n",
       "      <td>0.817941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sepal.Width</th>\n",
       "      <td>-0.117570</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.428440</td>\n",
       "      <td>-0.366126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Petal.Length</th>\n",
       "      <td>0.871754</td>\n",
       "      <td>-0.428440</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.962865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Petal.Width</th>\n",
       "      <td>0.817941</td>\n",
       "      <td>-0.366126</td>\n",
       "      <td>0.962865</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Sepal.Length  Sepal.Width  Petal.Length  Petal.Width\n",
       "Sepal.Length      1.000000    -0.117570      0.871754     0.817941\n",
       "Sepal.Width      -0.117570     1.000000     -0.428440    -0.366126\n",
       "Petal.Length      0.871754    -0.428440      1.000000     0.962865\n",
       "Petal.Width       0.817941    -0.366126      0.962865     1.000000"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "irisDataFrame.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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